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Topics in the Constructive Theory of Countable Markov Chains

present book is to provide methods, based on the construction of Lyapunov functions, of determining when a Markov chain is ergodic, null recurrent;

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Topics in the Constructive Theory of Countable Markov Chains

present book is to provide methods, based on the construction of Lyapunov functions, of determining when a Markov chain is ergodic, null recurrent;

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General Irreducible Markov Chains and Non-Negative Operators

The purpose of this book is to present the theory of general irreducible Markov chains and to point out the connection between this and the;

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Markov Processes for Stochastic Modeling

This book presents an algebraic development of the theory of countable state space Markov chains with discrete- and continuous-time;

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Martingales and Markov Chains

exposition of the theory, Martingales and Markov Chains: Solved Exercises and Elements of Theory presents, more than 100 exercises related to;

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Martingales and Markov Chains

exposition of the theory, Martingales and Markov Chains: Solved Exercises and Elements of Theory presents, more than 100 exercises related to;

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Markov Chains

Markov chains are central to the understanding of random processes. This is not only because they pervade the applications of random;

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Markov Chains

Markov Chains: Analytic and Monte Carlo Computations introduces the main notions related to Markov chains and provides explanations on how;

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Finite Markov Processes and Their Applications

finite Markov chain theory that offers examples of applicable models.The text advances to studies of two basic types of homogeneous finite;

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Mathematics of Probability

This book covers the basics of modern probability theory. It begins with probability theory on finite and countable sample spaces and then;

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Introduction to Hidden Semi-Markov Models

to the subject by first developing the theory of Markov processes in an elementary discrete time, finite state framework suitable for senior;

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Markov Chains

author uses quantifiable examples to illustrate how probability theory arrived at the concept of discrete-time and the Markov model from;

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Markov Chains And Dependability Theory

, Markov models, describing both basic results and specialised techniques. The authors first present both discrete and continuous time Markov;

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Elements Of Stochastic Modelling

of probability theory and then covers the following topics: Markov chains, Markov decision processes, jump Markov processes, elements of queueing theory;

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Topics in Dynamics and Ergodic Theory

comprises nine chapters on a range of important topics. These include: the role and usefulness of ultrafilters in ergodic theory, topological;

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Markov Chains

both discrete and continuous time Markov chains. The relationship between Markov chains of finite states and matrix theory will also be;

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Analysis of Computer and Communication Networks

, interconnection networks, and switch architectures and buffering strategies. This book covers the mathematical theory and techniques necessary for;

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Ergodic Behavior of Markov Processes

The general topic of this book is the ergodic behavior of Markov processes. A detailed introduction to methods for proving ergodicity and;

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A First Course in Probability and Markov Chains

in Probability and Markov Chains presents an introduction to the basic elements in probability and focuses on two main areas. The first part explores;

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Markov Processes and Applications

This well-written book provides a clear and accessible treatment of the theory of discrete and continuous-time Markov chains, with an;

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The Theory of Probability

to the problems discussed. Topics of this book include the axiomatic setup of probability theory, polynomial distribution, finite Markov;

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Markov Chains and Decision Processes for Engineers and Managers

prescriptive, with little justification for the steps of the algorithms used to solve Markov models. Providing a unified treatment of Markov chains and;

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Markov Chains and Decision Processes for Engineers and Managers

prescriptive, with little justification for the steps of the algorithms used to solve Markov models. Providing a unified treatment of Markov chains and;

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Introduction to the Numerical Solution of Markov Chains

detailed treatment of the numerical solution of Markov chains, William Stewart provides scientists on many levels with the power to put this theory;

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Markov Chains and Mixing Times

This book is an introduction to the modern approach to the theory of Markov chains. The main goal of this approach is to determine the rate;

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Markov Chains

spaces and their associated homogeneous Markov chains. The first part, an expository text on the foundations of the subject, is intended for post;

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Approximate Quantum Markov Chains

This book is an introduction to quantum Markov chains and explains how this concept is connected to the question of how well a lost quantum;

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